Asia
Primal-Dual Coupled Variance Reduction for Faster Distributionally Robust Optimization
We consider the penalized distributionally robust optimization (DRO) problem with a closed, convex uncertainty set, a setting that encompasses learning using f -DRO and spectral/ L-risk minimization.
GV-Rep: A Large-Scale Dataset for Genetic Variant Representation Learning
The development of deep learning approaches for modeling these multifactorial effects of GVs is still in its nascent stages, primarily due to the lack of comprehensive datasets that capture the intricate relationships between GVs and their downstream effects on complex traits.
Understanding Hallucinations in Diffusion Models through Mode Interpolation
But where do such hallucinations come from?
Semantic Density: Uncertainty Quantification for Large Language Models through Confidence Measurement in Semantic Space
A new framework is proposed in this paper to address these issues.
InfoRM: Mitigating Reward Hacking in RLHF via Information-Theoretic Reward Modeling Y uchun Miao
With the advent of large language models (LLMs), reinforcement learning from human feedback (RLHF) has emerged as a pivotal technological paradigm to align models' behaviors with human values [
